No abstract

In cases where the balance problem of an assembly line with the aim to distribute the work loads among the stations as equal as possible, the concept of entropy function can be used. In this paper, a typical assembly line balancing problem with different objective functions such as entropy-based objective function plus two more objective functions like equipment purchasing cost and worker time-dependent wage is formulated. The non-linear entropy-based objective function is approximated as a linear function using the bounded variable method of linear programming. A new hybrid fuzzy programming approach is proposed to solve the proposed multi-objective formulation efficiently. The extensive computational experiments on some test problems proves the efficiency of the proposed solution approach comparing to the available approaches of the literature.

This paper focuses on formulating a typical simple assembly line balancing problem. A new objective function based on a nonlinear entropy function is considered for the simple assembly line balancing problem for the first time. This objective function force the stations to have more similar total task processing time, so that the workers of the stations will have similar work load. Using a bounded variable approach, the nonlinear objective function is converted to an approximated linear objective function. Finally, efficiency of the linearized formulation of the entropy-based assembly line balancing problem is tested by a numerical example.